eff_plot <- Effect (focal.predictors = "IFN.g" , fit.overdisp, xlevels= list (IFN.g= seq (min (meta2$ IFN.g) - 1 ,max (meta2$ IFN.g) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
ggplot () +
geom_line (data = eff_data, aes (x = IFN.g, y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IFN.g, y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IFN.g, ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IFN-g (Severe) \n (Coeff: -0.14; P-value: 0.02)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()
eff_plot <- Effect (focal.predictors = "IL.13" , fit.overdisp, xlevels= list (IL.13= seq (min (meta2$ IL.13 ) - 1 ,max (meta2$ IL.13 ) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
ggplot () +
geom_line (data = eff_data, aes (x = IL.13 , y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IL.13 , y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IL.13 , ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IL-13 (Severe) \n (Coeff: -0.13; P-value: 0.01)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()
eff_plot <- Effect (focal.predictors = "IL.17" , fit.overdisp, xlevels= list (IL.17= seq (min (meta2$ IL.17 ) - 1 ,max (meta2$ IL.17 ) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
ggplot () +
geom_line (data = eff_data, aes (x = IL.17 , y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IL.17 , y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IL.17 , ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IL-17 (Severe) \n (Coeff: -0.17; P-value: 0.02)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()
eff_plot <- Effect (focal.predictors = "IL.1F7" , fit.overdisp, xlevels= list (IL.1F7= seq (min (meta2$ IL.1 F7) - 1 ,max (meta2$ IL.1 F7) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
ggplot () +
geom_line (data = eff_data, aes (x = IL.1 F7, y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IL.1 F7, y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IL.1 F7, ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IL-37 (Severe) \n (Coeff: 0.16; P-value: 0.04)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()
eff_plot <- Effect (focal.predictors = "IL.24" , fit.overdisp, xlevels= list (IL.24= seq (min (meta2$ IL.24 ) - 1 ,max (meta2$ IL.24 ) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
ggplot () +
geom_line (data = eff_data, aes (x = IL.24 , y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IL.24 , y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IL.24 , ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IL-24 (Severe) \n (Coeff: 0.06; P-value: 0.04)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()
eff_plot <- Effect (focal.predictors = "IL.4" , fit.overdisp, xlevels= list (IL.4= seq (min (meta2$ IL.4 ) - 1 ,max (meta2$ IL.4 ) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
ggplot () +
geom_line (data = eff_data, aes (x = IL.4 , y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IL.4 , y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IL.4 , ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IL-4 (Severe) \n (Coeff: 0.15; P-value: 0.04)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()
eff_plot <- Effect (focal.predictors = "IL.5" , fit.overdisp, xlevels= list (IL.5= seq (min (meta2$ IL.5 ) - 1 ,max (meta2$ IL.5 ) + 1 ,0.1 )))
eff_data <- as.data.frame (eff_plot)
# Create a ggplot with effects plot and data points
p <- ggplot () +
geom_line (data = eff_data, aes (x = IL.5 , y = fit), color = "blue" ) +
geom_point (data = meta2, aes (x = IL.5 , y = L_FeNO_Value), color = "black" , shape = 16 ) +
geom_ribbon (data = eff_data, aes (x = IL.5 , ymin = lower, ymax = upper), fill = "blue" , alpha = 0.08 ) +
labs (title = "IL-5 (Severe) \n (Coeff: 0.13; P-value: 0.01)" ,
x = expression ('log' [2 ] * '(Expression)' ),
y = "FeNO (ppb)" ) +
theme_bw ()